Designing acceptance single sampling plans: An optimization‐based approach under generalized beta distribution

Abstract

The availability of information that suppliers possess about the production process, as well as about the technical and economic consequences for customers, encourages the development and application of acceptance sampling plans that follow economic criteria, such as the Bayesian ones proposed in the literature. The combination of prior knowledge described by the prior distribution and empirical knowledge based on the sample leads to the decision to accept or reject the lot under inspection. The main purpose of this study was to derive acceptance sampling plans for attributes based on a prior generalized beta distribution following the economic criterion to minimize the expected total cost of quality. Specifically, a procedure is proposed to define the optimal sampling plan based on the technical characteristics of the production process and the costs inherent in the quality of the product. After the methodological aspects are described in detail, an extensive simulation study is reported that demonstrates how the optimal plan changes according to the main parameters, providing guidance for practitioners.

Acceptance Sampling Plans based on Percentiles of Exponentiated Inverse Kumaraswamy Distribution

“…It is clear evidence that a distribution with all three shape parameters (EIKD) provides comparatively minimum sample size like other distributions. The motive of any statistical quality measures is to optimise or minimise the consumer's and producer's risk, Facchinetti et al (15) explained the Designing of single acceptance sample plans in an optimization-based approach under generalized beta distribution. The execution and applicability of the sampling plans are discussed with an application to electric carts data by A.I.…”

Dynamic Acceptance Sampling Strategy Based on Product Quality Performance Using Examples from IC Test Factory

“…A cost function is an essential consideration for developing an acceptance sampling plan. Facchinetti et al used a generalized beta distribution to create acceptance sampling plans for attributes to minimize quality cost [21]. They proposed a method to identify the best plan based on the production process and quality costs, including a simulation to show how key parameters affect the optimal plan.…”